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This page covers the Framer CMS integration in Profound. After connecting your Framer project, the following actions become available as Agent steps for working with Framer CMS collections and items. Each step requires you to select a connected Framer Project from a dropdown.

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Create Item

Create a new CMS item in a Framer collection.Required inputs
  • Framer Project — Select the Framer project you connected in Profound from the dropdown
  • Collection — Select the collection from the dropdown
  • Field Data — The available fields are generated from the selected collection’s schema. See Working with Create Item Inputs.
The output includes the created item’s id, slug, draft, and field_data.
Tip: Use Get Collection first to inspect the collection schema and confirm which fields are required before creating an item.

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Supported Field Types

Framer’s dynamic schema means Profound adapts to your collection model. The following Framer CMS field types are currently supported when creating items:
Field TypeDescriptionSupported
Plain TextSingle-line textYes
Formatted TextRich text contentYes
DateDate fieldNo
LinkURL fieldYes
ImageImage assetNo
GalleryArray of imagesNo
ColorColor valueNo
ToggleTrue/false valueYes
NumberNumeric valueYes
OptionSingle-select optionYes
FileFile assetNo
ReferenceReference to another itemNo
Multi-ReferenceReference to multiple itemsNo

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Understanding Collection Schemas

Use Get Collection to inspect a collection’s schema before working with its items. The output includes:
  • Collection ID and Collection Name
  • readonly — whether the collection is read-only
  • managed_by — how the collection is managed
  • field_definitions — the fields configured on that collection
Each field definition includes:
  • id — the field’s internal Framer ID
  • name — the label shown in Framer
  • type — the field’s primary Framer type, such as string, formattedText, or number
  • required — whether the field is required
  • itemType — additional item information for compound field types when Framer provides it
Example collection output: 
{
  "collection": {
    "field_definitions": [
      {
        "id": "slug",
        "name": "Slug",
        "required": true,
        "type": "string",
        "itemType": null
      },
      {
        "id": "111111",
        "name": "Title",
        "required": true,
        "type": "string",
        "itemType": null
      },
      {
        "id": "222222",
        "name": "Content",
        "required": true,
        "type": "formattedText",
        "itemType": null
      }
    ],
    "id": "333333",
    "managed_by": "user",
    "name": "Example Collection",
    "readonly": false
  }
}

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Working with Create Item Inputs

When you select a Framer collection in Create Item, Profound renders inputs dynamically from that collection’s schema. For supported field types, you can fill in the values directly in the step UI. For example, a collection may expose fields such as:
  • Slug
  • Title
  • Content
  • Link
  • Name
  • Option
  • Count
  • Featured
If a collection includes required fields with unsupported types, the Create Item request will fail because Profound cannot provide values for those fields.
Note: Use Get Collection to confirm the field definitions before creating an item. If you need support for a Framer field type that is not currently supported, contact us and we can help evaluate your use case.

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Understanding Item Output

Framer item responses include top-level item fields such as:
  • id
  • slug
  • draft
  • field_data
The field_data object is keyed by field ID. Each entry includes the field’s human-readable name, type, and value. Example item output: 
{
  "item": {
    "draft": true,
    "field_data": {
      "111111": {
        "name": "Title",
        "type": "string",
        "value": "Example title",
        "valueByLocale": {}
      },
      "222222": {
        "name": "Featured",
        "type": "boolean",
        "value": true
      }
    },
    "id": "333333",
    "slug": "example-title"
  }
}

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Common Use Cases

  • Content Publishing: Create new Framer CMS items from AI-generated copy or structured data
  • Content Retrieval: Pull structured content from Framer collections for review, summarization, or downstream workflows
  • Workflow Preparation: Inspect collection schemas before building automations that depend on specific Framer fields